looks like the best way to incorporate truth in AI is to use some kind of RAG.
what are the state of the art ways to consume knowledge graphs?
and what is the best way to build a knowledge graph using AI?

RAG is strong, but state-of-the-art KG consumption uses hybrid methods: GraphRAG (LLMs query subgraphs), KG-augmented embeddings (entities + relations), and neuro-symbolic reasoning (LLMs + graph rules).
Best KG building with AI today is automated entity/relation extraction via LLMs, schema alignment, and continuous validation using human-in-the-loop + graph constraints.